Mitigating the water footprint of export cut flowers from the Lake Naivasha Basin, Kenya

Kenya’s cut-flower industry has been praised as an economic success as it contributed an annual average of US$141 million foreign exchange (7$ 352 million in 2005 alone. The industry also provides employment, income and infrastructure such as schools and hospitals for a large population around Lake Naivasha. On the other hand, the commercial farms have been blamed for causing a drop in the lake level and for putting the lake’s biodiversity at risk. The objective of this study is to quantify the water footprint within the Lake Naivasha Basin related to cut flowers and assess the potential for mitigating this footprint by involving cut-flower traders, retailers and consumers overseas. The water footprint of one rose flower is estimated to be 7-13 litres. The total virtual water export related to export of cut flowers from the Lake Naivasha Basin was 16 Mm3/yr during the period 1996-2005 (22% green water; 45% blue water; 33% grey water). Our findings show that, although the commercial farms around the lake have contributed to the decline in the lake level through water abstractions, both the commercial farms and the smallholder farms in the upper catchment are responsible for the lake pollution due to nutrient load. The\ud observed decline in the lake level and deterioration of the lake’s biodiversity calls for sustainable management of the basin through pricing water at its full cost and other regulatory measures

The green, blue and grey water footprint of crops and derived crop products

This study quantifies the green, blue and grey water footprint of global crop production in a spatially-explicit way for the period 1996–2005. The assessment improves upon earlier research by taking a high-resolution approach, estimating the water footprint of 126 crops at a 5 by 5 arc minute grid. We have used a grid-based dynamic water balance model to calculate crop water use over time, with a time step of one day. The model takes into account the daily soil water balance and climatic conditions for each grid cell. In addition, the water pollution associated with the use of nitrogen fertilizer in crop production is estimated for each grid cell. The crop evapotranspiration of additional 20 minor crops is calculated with the CROPWAT model. In addition, we have calculated the water footprint of more than two hundred derived crop products, including various flours, beverages, fibres and biofuels. We have used the water footprint assessment framework as in the guideline of the Water Footprint Network. \ud \ud Considering the water footprints of primary crops, we see that the global average water footprint per ton of crop increases from sugar crops (roughly 200 m3 ton−1), vegetables (300 m3 ton−1), roots and tubers (400 m3 ton−1), fruits (1000 m3 ton−1), cereals (1600 m3 ton−1), oil crops (2400 m3 ton−1) to pulses (4000 m3 ton−1). The water footprint varies, however, across different crops per crop category and per production region as well. Besides, if one considers the water footprint per kcal, the picture changes as well. When considered per ton of product, commodities with relatively large water footprints are: coffee, tea, cocoa, tobacco, spices, nuts, rubber and fibres. The analysis of water footprints of different biofuels shows that bio-ethanol has a lower water footprint (in m3 GJ−1) than biodiesel, which supports earlier analyses. The crop used matters significantly as well: the global average water footprint of bio-ethanol based on sugar beet amounts to 51 m3 GJ−1, while this is 121 m3 GJ−1 for maize. \ud \ud The global water footprint related to crop production in the period 1996–2005 was 7404 billion cubic meters per year (78 % green, 12 % blue, 10 % grey). A large total water footprint was calculated for wheat (1087 Gm3 yr−1), rice (992 Gm3 yr−1) and maize (770 Gm3 yr−1). Wheat and rice have the largest blue water footprints, together accounting for 45 % of the global blue water footprint. At country level, the total water footprint was largest for India (1047 Gm3 yr−1), China (967 Gm3 yr−1) and the USA (826 Gm3 yr−1). A relatively large total blue water footprint as a result of crop production is observed in the Indus river basin (117 Gm3 yr−1) and the Ganges river basin (108 Gm3 yr−1). The two basins together account for 25 % of the blue water footprint related to global crop production. Globally, rain-fed agriculture has a water footprint of 5173 Gm3 yr−1 (91 % green, 9 % grey); irrigated agriculture has a water footprint of 2230 Gm3 yr−1 (48 % green, 40 % blue, 12 % grey)

A global and high-resolution assessment of the green, blue and grey water footprint of wheat

The aim of this study is to estimate the green, blue and grey water footprint of wheat in a spatially-explicit way,\ud both from a production and consumption perspective. The assessment is global and improves upon earlier\ud research by taking a high-resolution approach, estimating the water footprint of the crop at a 5 by 5 arc minute\ud grid. We have used a grid-based dynamic water balance model to calculate crop water use over time, with a time\ud step of one day. The model takes into account the daily soil water balance and climatic conditions for each grid\ud cell. In addition, the water pollution associated with the use of nitrogen fertilizer in wheat production is\ud estimated for each grid cell. We have used the water footprint and virtual water flow assessment framework as\ud in the guideline of the Water Footprint Network (Hoekstra et al., 2009).\ud The global wheat production in the period 1996-2005 required about 1088 billion cubic meters of water per\ud year. The major portion of this water (70%) comes from green water, about 19% comes from blue water, and the\ud remaining 11% is grey water. The global average water footprint of wheat per ton of crop was 1830 m3/ton.\ud About 18% of the water footprint related to the production of wheat is meant not for domestic consumption but\ud for export. About 55% of the virtual water export comes from the USA, Canada and Australia alone. For the\ud period 1996-2005, the global average water saving from international trade in wheat products was 65 Gm3/yr.\ud A relatively large total blue water footprint as a result of wheat production is observed in the Ganges and Indus\ud river basins, which are known for their water stress problems. The two basins alone account for about 47% of\ud the blue water footprint related to global wheat production. About 93% of the water footprint of wheat\ud consumption in Japan lies in other countries, particularly the USA, Australia and Canada. In Italy, with an\ud average wheat consumption of 150 kg/yr per person, more than two times the word average, about 44% of the\ud total water footprint related to this wheat consumption lies outside Italy. The major part of this external water\ud footprint of Italy lies in France and the USA

The green and blue water footprint of paper products: methodological considerations and quantification

For a hardcopy of this report, printed in the Netherlands, an estimated 200 litres of water have been used. Water is required during different stages in the production process, from growing wood to processing pulp into the final consumer product. Most of the water is consumed in the forestry stage, where water consumption refers to the forest evapotranspiration. The water footprint during the manufacturing processes in the industrial stage consists of evaporation and contamination of ground- and surface water. In this report we assess water requirements for producing paper products using different types of wood and in different parts of the world. We quantify the combined green and blue water footprint of paper by considering the full supply chain; we do not include the grey water footprint in this study. The water footprint of printing and writing paper is estimated to be between 300 and 2600 m3/ton (2-13 litres for an A4 sheet). These figures account for the paper recovery rates as they currently are. The exact amount depends on the sort and origin of the paper used for printing. Without recovery, the global average water footprint of paper would be much larger; by using recovered paper an estimated 40% is saved globally. Further saving can be achieved by increasing the recovery percentages worldwide. For countries with a low recovered paper utilization rate a lot of room for reduction still remains. Some countries such as the Netherlands, Spain and Germany already use a lot of recovered paper. In addition, the global water footprint of paper can be reduced by choosing production sites and wood types that are more water-efficient. The findings presented in this report can be helpful in identifying the opportunities to reduce water footprints of paper consumption. This report also shows that the use of recovered paper may be very helpful in reducing water footprints

EEMCS final report for the causal modeling for air transport safety (CATS) project

This document reports on the work realized by the DIAM in relation to the completion of the CATS model as presented in Figure 1.6 and tries to explain some of the steps taken for its completion. The project spans over a period of time of three years. Intermediate reports have been presented throughout the project’s progress. These are presented in Appendix 1. In this report the continuous‐discrete distribution‐free BBNs are briefly discussed. The human reliability models developed for dealing with dependence in the model variables are described and the software application UniNet is presente

Optimizing Emergency Transportation through Multicommodity Quickest Paths

In transportation networks with limited capacities and travel times on the arcs, a class of problems attracting a growing scientific interest is represented by the optimal routing and scheduling of given amounts of flow to be transshipped from the origin points to the specific destinations in minimum time. Such problems are of particular concern to emergency transportation where evacuation plans seek to minimize the time evacuees need to clear the affected area and reach the safe zones. Flows over time approaches are among the most suitable mathematical tools to provide a modelling representation of these problems from a macroscopic point of view. Among them, the Quickest Path Problem (QPP), requires an origin-destination flow to be routed on a single path while taking into account inflow limits on the arcs and minimizing the makespan, namely, the time instant when the last unit of flow reaches its destination. In the context of emergency transport, the QPP represents a relevant modelling tool, since its solutions are based on unsplittable dynamic flows that can support the development of evacuation plans which are very easy to be correctly implemented, assigning one single evacuation path to a whole population. This way it is possible to prevent interferences, turbulence, and congestions that may affect the transportation process, worsening the overall clearing time. Nevertheless, the current state-of-the-art presents a lack of studies on multicommodity generalizations of the QPP, where network flows refer to various populations, possibly with different origins and destinations. In this paper we provide a contribution to fill this gap, by considering the Multicommodity Quickest Path Problem (MCQPP), where multiple commodities, each with its own origin, destination and demand, must be routed on a capacitated network with travel times on the arcs, while minimizing the overall makespan and allowing the flow associated to each commodity to be routed on a single path. For this optimization problem, we provide the first mathematical formulation in the scientific literature, based on mixed integer programming and encompassing specific features aimed at empowering the suitability of the arising solutions in real emergency transportation plans. A computational experience performed on a set of benchmark instances is then presented to provide a proof-of-concept for our original model and to evaluate the quality and suitability of the provided solutions together with the required computational effort. Most of the instances are solved at the optimum by a commercial MIP solver, fed with a lower bound deriving from the optimal makespan of a splittable-flow relaxation of the MCQPP

Multi-objective road pricing: a cooperative and competitive bilevel optimization approach

Costs associated with traffic externalities such as congestion, air pollution, noise, safety, etcetera are becoming unbearable. The Braess paradox shows that combating congestion by adding infrastructure may not improve traffic conditions, and geographical and/or financial constraints may not allow infrastructure expansion. Road pricing presents an alternative to combat traffic externalities. The traditional way of road pricing, namely congestion charging, may create negative benefits for society. In this effect, we develop a flexible pricing scheme internalizing costs arising from all externalities. Using a game theoretical approach, we extend the single authority road pricing scheme to a pricing scheme with multiple authorities/regions (with likely contradicting objectives)

Marangoni driven turbulence in high energy surface melting processes

Experimental observations of high-energy surface melting processes, such as laser welding, have revealed unsteady, often violent, motion of the free surface of the melt pool. Surprisingly, no similar observations have been reported in numerical simulation studies of such flows. Moreover, the published simulation results fail to predict the post-solidification pool shape without adapting non-physical values for input parameters, suggesting the neglect of significant physics in the models employed. The experimentally observed violent flow surface instabilities, scaling analyses for the occurrence of turbulence in Marangoni driven flows, and the fact that in simulations transport coefficients generally have to be increased by an order of magnitude to match experimentally observed pool shapes, suggest the common assumption of laminar flow in the pool may not hold, and that the flow is actually turbulent. Here, we use direct numerical simulations (DNS) to investigate the role of turbulence in laser melting of a steel alloy with surface active elements. Our results reveal the presence of two competing vortices driven by thermocapillary forces towards a local surface tension maximum. The jet away from this location at the free surface, separating the two vortices, is found to be unstable and highly oscillatory, indeed leading to turbulence-like flow in the pool. The resulting additional heat transport, however, is insufficient to account for the observed differences in pool shapes between experiment and simulations

Water footprint of cotton, wheat and rice production in Central Asia

The hydrology of the Aral Sea Basin during the past few decades has been largely determined by the decision to\ud develop irrigated agriculture on a large scale to produce cotton for export in the 1960s. The irrigated area has\ud grown to 8 million hectares, using practically the entire available flow of the two main rivers, the Amu Darya\ud and Syr Darya. Almost two decades after the disintegration of the Soviet Union, the five states of the Aral Sea\ud Basin face the challenge of restoring a sustainable equilibrium while offering development opportunities for an\ud increasing population. Sustainable water management is thus an imperative that will require coordinated\ud political action of all the states involved.\ud The Soviet Union established its cotton-producing areas in Uzbekistan, Turkmenistan, Tajikistan, and\ud Kyrgyzstan. Today, while cotton remains relatively important, cereal production to reduce imports has become a\ud priority in all four nations. The cotton crop area has decreased over the past ten years, while that of winter wheat\ud – the main grain crop – has doubled. At 39 per cent of the total (blue and green) water consumption in\ud agriculture, wheat is the largest water-consuming crop in the five basin states, followed by cotton at 33 per cent.\ud The present study analyses the water footprint of Central Asian cotton (Gossypium hirsutum L.), wheat\ud (Triticum aestivum L.) and rice (Oryza sativa L.) production, differentiating between the green and blue\ud components, in order to know how the scarce water resources in the region are apparently allocated